The Democratization of AI and Big Data

The market chatter around Big Data and AI has increased rapidly in the last few years to the point that it features almost daily in mainstream media. A quick look at some of the numbers banded about and it’s easy to see why (although not always easy to prove their veracity). For Big Data a quick search for articles online will return figures like; 2.7 Zetabytes of data exist in the digital universe today, 571 new websites are created every minute of the day, by 2020 business transactions on the internet will reach 450 billion per day. For AI, the results are no less impressive; there was more than $300 million in venture capital invested in AI startups in 2014, a 300% increase over the year before; by this year, 75% of developer teams will include AI functionality in one or more applications or services; by 2020, 30% of all companies will employ AI to augment at least one of their primary sales processes.

However, for many people not directly involved in the tech industry or the IT department of a large multinational it’s sometimes difficult to see how these claims relate in any way to their day to day tasks. For most companies the issue is, until recently, to do anything innovative with big data or AI you needed highly skilled data scientists versed in seemingly impenetrable technologies like NoSQL, R, MapReduce or Scala. And these guys are hard to come by, expensive, and not getting cheaper. IBM predicts that demand for data professionals in the US alone will reach 2.7 million by 2020.

However, that’s not the complete picture. Much in the same way computers began entering the business world as the preserve of large corporations like J Lyons & Company and the U. S. Census Bureau, were later more widely used as companies that could afford the huge cost of buying them provided services to others, and finally the productization of computers by the likes of IBM allowed almost every organisation to buy their own, Big Data and AI technologies are going through the same process of democratization.

The major three Cloud data providers Microsoft, Google and Amazon are amongst a host of providers that now offer scalable and affordable Big Data platforms that can be spun up in seconds. The commoditization of these services is also driving down the price of managing large datasets to the point that it is affordable for even small companies. The picture for AI is also changing rapidly. In the last few years all three major Cloud providers have started offering API driven AI services bound into their cloud platforms, and their offerings get more sophisticated by the day. More importantly, those Big Data platforms and AI API’s are now becoming easily accessible to more traditional development environments like .NET and Java. This means that millions of traditional developers can now leverage Big Data and AI without leaving the comfort of their familiar development environment.

All this drives the availability of tools that leverage Big Data and AI technologies down to smaller organisations. To date, adoption has primarily been larger companies outside the tech industry taking AI capabilities offered by technology vendors and applying them to their business. For instance, retailers like Dixons Carphone and Ocado adopting natural language API’s from the big cloud providers to deliver chat interfaces on their websites, or Renaults Formula 1 team using Microsoft machine learning platform to automate predictions of how their car will perform. However, these same platforms allow AI and Big Data technologies to be embedded in off the shelf products, and that offers the prospect of much greater disruption for every industry. Personal assistants like Siri, Alexa, Cortana and Google Assistant are the forerunners, but developers are increasingly building these technologies into more and more business application and consumer products. Predicting how the world will change when AI and Big Data technology is democratised to the point that it is pervasive in every aspect of our lives is impossible, but it’s probably safe to say the changes we’ve seen already are the tip of the iceberg.

DataPA will be an exhibitor at DataSummit18.

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